A Comprehensive Monte Carlo-Simulated Dataset of WAXD Patterns of Wood Cellulose Microfibrils by Ricardo Baettig, Ben Ingram

“…It enables the development, validation, and benchmarking of novel algorithms and machine learning models for MFA prediction from diffraction patterns. …”
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Research on inter-plant weeding control in peanut at LADRC based on IACO-PSO optimization by Xiaolong Zhang, Hongzhen Xu, Jiaodi Liu, Longzhe Quan, Lichang Zhang, Bang Zhang

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The relationship between kinship and foster placement on mental health indicators in children and youth seeking treatment by Shannon L. Stewart, Boden Brock, Jordyn Manis, Aadhiya Vasudeva, Jeffrey W. Poss

“…These assessments include a variety of embedded evidence-informed scales and algorithms to examine the mental health needs, preferences and strengths of these vulnerable children. …”
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Multi-Omics and Experimental Validation Identify GPX7 and Glutathione-Associated Oxidative Stress as Potential Biomarkers in Ischemic Stroke by Tianzhi Li, Sijie Zhang, Jinshan He, Hongyan Li, Jingsong Kang

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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

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Comparative analysis of reinforcement learning and artificial neural networks for inverter control in improving the performance of grid-connected photovoltaic systems by Saad A. Mohamed Abdelwahab, Hossam Eldin Khairy, Hossam Yousef, Samia Abdafatah, Moayed Mohamed

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Automated Segmentation of Breast Cancer Focal Lesions on Ultrasound Images by Dmitry Pasynkov, Ivan Egoshin, Alexey Kolchev, Ivan Kliouchkin, Olga Pasynkova, Zahraa Saad, Anis Daou, Esam Mohamed Abuzenar

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Automated Overtake Assist System Using YOLOv4 and Mask R-CNN for Enhanced Autonomous Driving by Navya Thirumaleshwar Hegde, Kapileswar Rana, S. S. Barath, Florence Nishmitha, Vishnu G. Nair

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Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning by Feng Lu, Yingying Liu, Zhen Chen, Shuning Chen, Weidong Liang, Fuzhou Hua, Maolin Zhong, Lifeng Wang

“…Validation through qRT-PCR confirmed the differential expression of four genes (Abca1, Glipr1, Il10ra, and Cdh1), which demonstrated strong predictive performance. Pathway enrichment of GRRDEGs was analyzed using GO, KEGG, and Bayesian network methods, and immune cell infiltration was assessed via CIBERSORT. …”
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QFCOI-Enhancing Objective Quality Assessment for Compressed Omnidirectional Images With Fusion of Measures by Marek Simka, Ladislav Polak, Adam Zizien, Karel Fliegel

“…The feature metrics selection was based on statistical performance and ability to capture key aspects of image quality, including structural preservation, visual information fidelity, and artifact sensitivity. To optimize predictive performance of QFCOI, a genetic algorithm was utilized to determine optimal weight coefficients, maximizing the monotonic correlation with subjective quality scores. …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…The findings contribute to a more accurate and reliable identification of faults, offering significant advancements in the field of machinery health monitoring and predictive maintenance.…”
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Validation study of bullous pemphigoid and pemphigus vulgaris recording in routinely collected electronic primary healthcare records in England by Yana Vinogradova, Julia Hippisley-Cox, Sonia Gran, Sinéad M Langan, Monica S M Persson, Karen E Harman, Kim S Thomas

“…We assessed the positive predictive value (PPV) for bullous pemphigoid and pemphigus vulgaris primary care Read codes in the Clinical Practice Research Datalink (CPRD) using linked inpatient data (Hospital Episode Statistics (HES)) as the diagnostic benchmark.Setting Adult participants with bullous pemphigoid or pemphigus vulgaris registered with HES-linked general practices in England between January 1998 and December 2017. …”
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A Comprehensive Review of the Main Heavyweight and Lightweight SDLC for Big Data Analytics Systems (BDAS) by David Alejandro Montoya-Murillo, Sergio Galvan-Cruz, Manuel Mora, Estela Lizbeth Munoz Andrade

“…Big Data Analytics Systems (BDAS) are software systems developed with descriptive, predictive, or prescriptive decision-making purposes, and currently are implemented in diverse domains – i.e. …”
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Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions by Shumaila Javaid, Ruhul Amin Khalil, Nasir Saeed, Bin He, Mohamed-Slim Alouini

“…We outline the current architecture of ISATNs and highlight the significant role LLMs can play in optimizing data flow, signal processing, and network management to advance 5G/6G communication technologies through advanced predictive algorithms and real-time decision-making. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…Empirically, we draw on a cross-sectional research project, assessing the predictive power of linguistic data processing algorithms and the experiences of financial analysts in cost structuring contexts. …”
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Modeling Universal Thermal Climate Index Thermal Stress in Iran’s Hot Zones Using Neural Networks and Naïve Bayes by Sajad Zare, Reza Esmaeili, Rasoul Hemmatjo

“…Conclusion: In the models for hot-dry regions, both algorithms predicted Ta and then Tmrt as the principal factors. …”
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Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

“…Introduction: Artificial intelligence (AI) is making waves in health care, with ECGs and other imaging data leveraged to diagnose or predict cardiovascular diseases (CVDs). Materials and methods: Various AI models as well as algorithms, such as machine learning (ML) and deep learning (DL) algorithms, have shown good results in the detection of diseases like heart failure, atrial fibrillation, coronary artery disease, and valvular heart disease. …”
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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…The Mountain Gazelle Optimizer is a recently developed metaheuristic algorithm that simulates the foraging behaviors of Mountain Gazelles. …”
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Wave propagation-based tests for concrete piles – an overview by Reham Samaan, Abdelsalaam Mokhtar, Mohamed Saafan, Ahmed Ebid

“…This investigation establishes the practical and theoretical basis for implementing advanced machine learning predictive models that combine previous records with pattern recognition algorithms, potentially converting traditional PIT interpretation from an uncertain process to a reliable and precise evaluation system. …”
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Detecting anomalies in graph networks on digital markets. by Agata Skorupka

“…Methods are compared against each other, and state-of-the-art results from the literature and a new algorithm is proposed. The goal is to find an efficient method suitable for threat detection, both in terms of predictive performance and computational efficiency. …”
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